In order to be able to assess the behavior of a plant during operation or retrospectively, it is necessary to store a mostly large number of process signals produced during operation and to analyze their characteristics as function of time.
These process signals usually originate from different components and must be combined into a data stock and assessed according to defined evaluation criteria.
After only a short time, even an average sized plant will have generated a multitude of process signals whose storage and further processing e.g. for diagnostic purposes quickly uses up or overextends the resources available.
In these circumstances bottlenecks generally arise directly at storage due to the enormous storage space requirement, during further processing e.g. by means of analysis algorithms, —the algorithms having to process a very large data stock, or during transmission of the stored process signals to an evaluation computer which interrogates the stored process signals e.g. by remote access, particularly via the Internet.
Particularly in the last mentioned case, the transmission times are very long if the stock of stored process signals is very large.
To overcome these problems, a known solution is to subject the process signals to compression before storing them, so that the storage space required is reduced.
The disadvantage of this is that, particularly in the case of compression methods having a high compression rate, information concerning the time response of the process signals is lost which is crucial for detailed examination of a plant operating state.